Managing dialog data providers

ABSTRACT

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for managing dialogs. In one aspect, a method includes receiving a request associated with a task from a user device; submitting the request to each of a plurality of distinct data providers; receiving a plurality of suggested dialog responses from two or more of the data providers; scoring the one or more suggested dialog responses based on one or more scoring factors; determining a particular dialog response to provide to the user based on the scoring; and providing the determined dialog response to the user device.

BACKGROUND

This specification relates to dialogs.

Conventional mobile devices can include software to respond to speech ofa user of the mobile device. The speech can typically includeinstructions to the mobile device to call a phone number, text a phonenumber, or search for information on the mobile device or the internet.The software can provide audio output from the mobile device confirmingthe instructions. The mobile device can provide the received speech to aserver system for processing and receiving information identifyingoperations to perform.

SUMMARY

This specification describes technologies relating to managing dialogsincluding moderating between different data providers. In general, oneinnovative aspect of the subject matter described in this specificationcan be embodied in methods that include the actions of receiving arequest associated with a task from a user device; submitting therequest to each of a plurality of distinct data providers; receiving oneor more suggested dialog responses from one or more of the dataproviders; scoring the one or more suggested dialog responses based onone or more scoring factors; determining a particular dialog response toprovide to the user based on the scoring; and providing the selecteddialog response to the user device.

Other embodiments of this aspect include corresponding computer systems,apparatus, and computer programs recorded on one or more computerstorage devices, each configured to perform the actions of the methods.For a system of one or more computers to be configured to performparticular operations or actions means that the system has installed onit software, firmware, hardware, or a combination of them that inoperation cause the system to perform the operations or actions. For oneor more computer programs to be configured to perform particularoperations or actions means that the one or more programs includeinstructions that, when executed by data processing apparatus, cause theapparatus to perform the operations or actions.

The foregoing and other embodiments can each optionally include one ormore of the following features, alone or in combination. In particular,one embodiment includes all the following features in combination. Themethod includes: updating a state of a dialog based on the selecteddialog response. The received request is a voice input and wherein themethod comprises converting the voice input request to text prior tosubmitting the request to the plurality of data providers. The methodfurther includes: determining if the dialog requires further responsesfrom the user device and in response to determining that no furtherresponses are required, completing the task requested by the user. Eachdata provider independently analyzes the request according to acorresponding data model. In response to determining that none of therespective scores for the plurality of suggested dialog responsessatisfy a threshold amount, synthesizing a response to provide to theuser device to ascertain the user intent. Determining a particulardialog response to provide to the user based on the scoring includesdisqualifying a suggested dialog response having a score that is lowerthan a threshold amount and also disqualifying all suggested dialogresponses that refer to the suggested dialog response

Particular embodiments of the subject matter described in thisspecification can be implemented so as to realize one or more of thefollowing advantages. Dialog management is improved for responding totasks by moderating between different data providers that can respond toa user input. In particular, the different data providers havingdifferent strengths and weaknesses can be leveraged. This allowsspecialized data providers while also providing flexibility in the typesof user inputs that can be interpreted. Additionally, dialog managementcan allow receiving parallel responses from the different data providersand optionally aggregating the received responses. Additionally, dataproviders can be heterogeneous with respect to implementation, e.g.,they may be generated by different vendors or be built using differenttechnologies, or be accessible through different networks (like localvs. far-flung). As long as each data provider provides data using theprescribed interface, the system can combine their data into a unifieddialog response.

The details of one or more embodiments of the subject matter describedin this specification are set forth in the accompanying drawings and thedescription below. Other features, aspects, and advantages of thesubject matter will become apparent from the description, the drawings,and the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an example system for managing a dialog.

FIG. 2 is a flow diagram of an example process for managing a dialog.

Like reference numbers and designations in the various drawings indicatelike elements.

DETAILED DESCRIPTION

Users can provide voice instructions to a device to perform a particulartask, for example, generating a calendar item, placing a call or text,or searching for particular information. Performing the task, by thedevice or by a system in communication with the device, can be driven bya conversational dialog that asks the user questions for one or morevalues needed to complete the task, analogous to filling out fields of aform.

For example, a sample dialog for a calendar task can be:

-   -   User: [create an alarm]    -   Device/system: What time would you like your alarm?    -   User: [3:00 pm]    -   Device/system: I've generated an alarm for 3:00 μm.

In response to the user input of the command to create the alarm, thesystem interprets the command as requesting a task to set an alarm at aparticular time. In particular, a data provider for performing tasks caninterpret the received voice input and direct a specific dialog towardinformation necessary to complete the task, e.g., requesting a time forthe alarm.

In another example dialog, the user can be seeking particularinformation:

-   -   User: [When does the Giants game start?]    -   Device/system: Do you mean the San Francisco Giants or the New        York Giants?

Here, the system understands the question from the user as a sportsscheduling query, but there is ambiguity as to which “Giants” the usermeans. The dialog response requests a clarification of which “Giants”sports team the user is referring to. Once clarified, the dialog cancontinue to provide scheduling information, for example, as identifiedby a search system.

In some cases, the user input can change from one type of task topotentially another type of task depending on how the dialog systeminterprets the voice input. For example:

-   -   User: [Set an alarm]    -   Device/system: What time would you like your alarm?    -   User: [When does the Giants game start?]

In this example, the user's second response can be interpreted in morethan one way depending on which data provider is triggered by the voiceinput. For example, a tasks data provider can interpret voice inputsrelated to creating an alarm, but not consider the second input on theGiants game to be a noisy or nonsense response because it doesn't relateto the expected input for the alarm task dialog. However, another dataprovider that can interpret sports related voice inputs can process theGiants game schedule question. This specification describes techniquesfor moderating and combining dialog responses from multiple dataproviders.

FIG. 1 is an example system 100 for managing a dialog. The system 100includes a user 102, a user device 104, a dialog system 106, andmultiple data providers 124 a, 124 b, to 124 n. The user device 104 andthe dialog system 106 care in communication though a network 103, e.g.,the internet.

The user device 104 can be one of a number of suitable devices includinga mobile device, a wearable computer, a tablet, a hybrid, a laptop, ordesktop computer. The user device 104 can receive interactions, bothverbal, e.g., voice inputs, and non-verbal from the user 102. Inparticular, the user device 104 includes a microphone 108 configured toreceive voice inputs from the user 102. The user device 104 can alsoinclude one or more speakers configured to broadcast dialog questions inresponse to received user request. Only a single user device is shownfor clarity. However, there can be many user devices associated withcorresponding distinct users. Each of these user devices can be incommunication with the dialog system 106 through the network 103.

The user device 104 further includes a user interface 110. The userinterface 110 can present information to the user including some or allof content associated with a dialog in response to a user request. Thedialog 112 defines a number of responses, e.g., questions for values,needed to perform a task requested by the user. Particular questions orother content of the dialog 112 can be presented to the user in aparticular order, for example, though a sequence of audio questionsbroadcast by the one or more speakers or displayed in the user interface110.

In some other implementations, the user device includes a speechanalysis engine to convert received voice inputs to the microphone 108into text prior to transmission to the dialog system 106.

The dialog system 106 can be one or more computing resources, e.g., oneor more computing systems, or virtual machines executing on one or morecomputing systems, in communication with the user device 104 through thenetwork 103. The dialog system 106 includes a dialog management engine114 and a speech analysis engine 116.

The speech analysis engine 116 can use a suitable speech-to-text processto convert the received voice inputs 118 into a text string. In someimplementations, the speech analysis engine 116 emits text that can beprocessed by one or more parsers to identify one or more meanings, e.g.,by generating a parse tree. The meaning of the audio as converted totext can be used by one or more data providers to identify a particulartask to perform in response to a received request.

The dialog management engine 114 manages one or more dialogs associatedwith a requested task. This includes maintaining a state of the dialog,e.g., what question is being answered, so that the speech analysisengine 116 can properly interpret received audio associated with thedialog based on the current context provided by the state. In addition,the dialog management engine 114 determines a response to an incomingvoice input based on the state of the dialog as well as theinterpretation of the voice input by one or more of the data providers124 a, 124 b, and 124 n, representing a data provider 1, data provider2, and data provider N where N is some integer representing a totalnumber of data providers that can provide input to the dialog system106.

Each of these data providers 124 a-n represents a backend system that isconfigured to independently interpret voice inputs according to aparticular data model for that data provider. For example, a first dataprovider can be a tasks provider that has a data model configured tointerpret voice queries related to particular tasks such as creating acalendar entry, setting an alarm, placing a telephone call, orgenerating a text message. The tasks data provider expects user inputsassociated with particular tasks and recognizes voice inputs associatedwith those expected user inputs. A second data provider can be a sportsprovider that has a data model configured to interpret voice queriesrelated to particular sports topics including teams and scores. Otherdata providers can include search data providers that are focused onparticular types of information, e.g., local businesses, socialnetworking information, or commercial data such as shoppingopportunities.

In response to a voice input that is received from the user device 104and processed by the voice analysis engine 116, one or more of the dataproviders 124 can interpret the received input and provide a dialogresponse to the dialog management engine 114. The dialog managementengine 114 then determines which dialog response to provide to the userdevice 104. Different ways of responding are described in greater detailbelow.

Each data provider 124 a-n suggests a dialog response based on theinterpretation of a received input according to the data model of thecorresponding data provider. The dialog response, and optionally otherinformation such as an expected response from the user 102, can beencoded in a data structure according to a particular data format. Insome implementations, this information is encoded in a protocol bufferreferred to in this specification as a DialogTurnIntent (“DTI”). Forconvenience, DTI will be used throughout, but other suitable encodeddata structures can be used.

For example, in a dialog for a task of composing an e-mail message, onequestion of the dialog can be a request for a subject of the e-mail. Thetasks data provider can create a DTI where the question to the user is aprompt for a subject. The DTI is provided to the dialog managementengine 114 and sent to the user device 104 where it can be presented tothe user 102, for example, as a visual question in the user interface,e.g., “What is the subject?” or as an audio question emitted from thespeakers e.g., “What would you like the subject to be?”

The dialog management engine 114 can send (120) more than one DTI to theuser device 102. In particular, the DTIs can include not only thecurrent prompt to the user, but other DTIs related to other fieldsnecessary to complete the dialog for the requested task. For example,when the dialog management engine 114 sends the “prompt for subject” DTIit can also send a DTI for a subsequent question in the dialog, e.g., a“prompt for message body” DTI.

FIG. 2 is a flow diagram of an example process 200 for managing adialog. For convenience, the process 200 will be described as beingperformed by a system of one or more computers, located in one or morelocations, and programmed appropriately in accordance with thisspecification. For example, a dialog system, e.g., the dialog system 106of FIG. 1 , appropriately programmed, can perform the process 200.

The system receives an input including a request (202). The request canbe received as a voice input provided by a user to a user device or amanual input to the user device, e.g., user device 104 of FIG. 1 andtransmitted to the system. In some implementations, a user voice inputcan be converted to text by the user device prior to being sent to thesystem. The task can be, for example, generating a calendar item,setting an alarm, generating an e-mail, placing a call or text, orsearching for particular information.

The system provides the request to multiple data providers (204). Eachdata provider can be configured to interpret different types of requestsusing a particular data model. Thus, the received request can beinterpreted differently by different data providers depending on how therequest is processed according to the respective data models.

The system receives a suggested dialog response from one or more of thedata providers (206). Each data provider independently analyzes therequest according to a respective data model. The data model can includea model trained on a specific collection of data associated with aparticular type of information or action. The request may trigger aresponse by some but not all data providers of the multiple dataproviders. Thus, a voice input request for a baseball game schedule maytrigger a suggested dialog response from a data provider trained toprovide sports related responses but not trigger a data provider trainedto provide weather information because the voice input does not match anexpected request associated with weather information. In someimplementations, a data provider may provide a response for anunrecognized voice input, for example, indicating that the input was notunderstood and ask the user to repeat the response.

The one or more data providers can provide the suggested dialog responsein the form of a DTI that includes the suggested response to provide tothe user device.

In some implementations, each data provider is able to view thesuggested dialog responses provided by other data providers. Inresponse, a given data provider can modify or add suggested dialogresponses based on the dialog responses of other data providers. Forexample, a task data provider can suggest a response that is based onthe suggested response of a search data provider, e.g., suggesting atime to set an alarm based on a response from a search data providerproviding a time for a sports game. Additionally, in someimplementations, each data provider can provide multiple suggesteddialog responses. For example, each response to can based on the contextof a suggested response of another data provider as well as a responsethat ignores suggestions of other data providers.

The system determines which dialog response to select (208). Inparticular, the system analyzes all of the suggested dialog responsesand determine which suggested dialog response is the most appropriate toselect. The analysis is performed after receiving all of the individualsuggestions from the data providers but before any dialog responses aresent to the user device. The system can score each suggested responsebased on one or more factors. Various factors can be used to score thesuggested dialog responses to select including one or more of logs-basedtuning of likely user intention, user personalization models, scoresindicating the likelihood of each data provider's semanticinterpretation, or an overall dialog strategy configuration thatdetermines the balance between careful accordance and minimizing anumber of questions asked as part of the dialog.

In some implementations, the data providers include confidence scoreswith their results. The confidence scores can be used to determine whichsuggested response to select. In some other implementations, otherselection factors can include the length of the dialog conversation andthe history of the dialog conversation. For example, if the user isasking the same question multiple times the data provider may not beproviding the information the user is seeking and a different dataprovider can be selected instead.

In some implementations, a selection factor is a likelihood that theinformation being considered is something that a normal user would beinterested in (as opposed to esoterica). For example, if there is nosuch sports team as Giants, we should consider that the user wasmisunderstood before doing a search for e.g., “giants that play”.

In some implementations, a selection factor is a quality of theinformation being considered. The quality can be based, for example, onwhether the data provider obtained the information from a structuredsource, e.g., official baseball schedule service, or an unstructuredsource, e.g., blogs by random people.

In some implementations, a selection factor is based on pragmatics andtask planning. For example, if the system doesn't know what time eitherof the Giants teams play, the system shouldn't ask the user which Giantsthey mean, because the answer would not have any impact on the broadertask.

In some implementations, a selection factor is derived based onrelevance of the information being considered to the user query. Forexample, if the “Giants” were only an obscure team in a far off country,the system should consider them irrelevant.

In some implementations, a selection factor is based on whether adetermination is made that the query is ambiguous enough that the systemshould ask the user to clarify their intention, without annoying them byasking dumb/obvious questions. The determination can be made, forexample, based on geographic information about where the user islocated, personalization, e.g., user history discussing SF Giants vs. NYGiants, or context e.g., only one of the teams has a game schedulessoon.

In some implementations, if a particular suggested dialog responsescores lowly based on these factors, e.g., the suggested dialog responsefails to satisfy a particular threshold score, the dialog managementengine can not only disqualify that suggested dialog response but alsoany other suggested dialog responses that refer to the suggested dialogresponse. In some implementations, if the scores from two or more dataproviders are not distinguishable by a specified threshold amount, thedialog management engine can generate an intent disambiguation questionas the dialog response.

The system provides the selected dialog response to the user device(210) and updates a state of the dialog (212). The dialog response sentto the user device can include the DTI of the selected dialog responsethat indicates the response to be presented to the user on the userdevice. This response can be synthesized into a voice response orpresented on a user interface of the user device. In someimplementations, the response is sent along with additional information,for example, one or more search results associated with the dialogresponse. For example, if the dialog response is based on a dataprovider's search or relevant web pages, links to those web pages can beprovided along with the dialog response.

The updated state of the dialog can be used to determine a next portionof the dialog to send in response to received user responses.Additionally, the updated state of the dialog can provide context to theanalysis of a subsequent voice input received from the user device suchthat the voice input can be properly interpreted.

The system completes the request when appropriate dialogs are completed(214).

The system can determine whether there are additional values needed orwhether the dialog is complete. If there are additional values neededone or more additional DTIs may be sent to the user device or the systemmay wait for additional responses from the user device. If there are noadditional values needed, the system can complete the task, for example,by generating a calendar entry or e-mail message, or by providingparticular requested information. The completed task can be sent to theuser device for approval before being executed or can be automaticallyperformed.

There are a number of different ways the system can interpret inputsbased on the suggestions of the different data providers and the scoringapplied. The following describes some example scenarios for interpretinga user input:

Scenario 1:

-   -   User: [Set an alarm]    -   System/device: What time would you like your alarm?    -   User: [What time does the Giants game start?]

In this example, the data providers can include a tasks provider, asports provider, and a web answers provider. If the system determinesthat the dialog suggestions of the sports and web data providers arenoisy, these responses should be disfavored and the task provider thatwas already triggered should govern the dialog. This can result in aresponse such as:

-   -   System/device: Sorry, I didn't get that. What time would you        like your alarm?

Scenario 2:

In this scenario, the user is asking a side question because they wantto watch the Giants game. The system has a higher confidence in the webanswers this time as reflected in the score for the correspondingsuggested dialog response and therefore it is selected over the sportsprovider and the task provider to create a blended dialog:

-   -   User: [Set an alarm]    -   System/device: What time would you like your alarm?    -   User: [What time does the Giants game start?]    -   System/device: Based on the results below, the Giants game        begins today at 3 pm. Set your alarm for then?

Scenario 3:

Similar to scenario 2, except that the dialog management enginesynthesizes a new question to determine whether the user meant to changetopics or if they are still interested in the original task:

-   -   User: [Set an alarm]    -   System/device: What time would you like your alarm?    -   User: [What time does the Giants game start?]    -   System/device: Based on the results below, the Giants game        begins today at 3 pm. Do you still want to set an alarm?

Scenario 4:

In scenario 4, the user is asking a side question because they want towatch the Giants game. Even though the web answer provider provides atime as a suggested answer, the system allows a sports provider'ssuggestion, which scored higher, to clear ambiguity and confirm theright entity. Maintaining the intent to set an alarm, the followingblended dialog can occur:

-   -   User: [Set an alarm]    -   System/device: What time would you like your alarm?    -   User: [What time does the Giants game start?]    -   System/device: Do you mean the SF giants or the New York Giants?    -   User: [SF Giants]    -   System/device: Based on the results below, the SF Giants play at        3 pm. Set your alarm for then?

Scenario 5:

In this scenario, the user is changing the subject and no longer wantsto set an alarm. Here, the dialog management engine is confident thatthe web answers provider identifying the time of the Giants game, whichscores higher than the other suggested dialog responses and does notsuggest an alarm that continues the prior task.

-   -   User: [Set an alarm]    -   System/device: What time would you like your alarm?    -   User: [What time does the Giants game start?]    -   System/device: Based on the results below, the Giants game        begins today at 3 pm.

Scenario 6:

In this scenario the user is changing the subject and no longer wants toset an alarm. The dialog management engine uses the highest scoringsuggestion of the sports data provider to clarify the entity and thenthe web answers to identify the time. No alarm is suggested.

-   -   User: [Set an alarm]    -   System/device: What time would you like your alarm?    -   User: [What time does the Giants game start?]    -   System/device: Do you mean the SF Giants or the New York Giants?    -   User: [SF Giants]    -   System/device: Based on the results below, the Giants game        begins today at 3 pm.

Scenario 7:

In this scenario, the dialog management engine may synthesize a questionto disambiguate whether the user is changing the subject or asking aside question. This may occur because two or more suggested responsesscored too close to determine which one should be favored.

-   -   User: [Set an alarm]    -   System/device: What time would you like your alarm?

User: [What time does the Giants game start?]

System/device: Wait, do you want to finish setting up your alarm or areyou trying to schedule your alarm around the game?

In each of these scenarios, the various data providers suggest one ormore dialog responses based on the user input. Additionally, the dataproviders can suggest multiple dialog responses based on the suggesteddialog responses of other data providers.

Referring to the example scenarios above, a tasks provider can provide asuggested dialog response of “sorry, I didn't get that. What time wouldyou like your alarm?” This corresponds to scenario 1 above.

In response to the task provider becoming aware of a suggested dialogresponse was sent by a web answers provider, the tasks provider cangenerate another suggested dialog response that refers to the webanswers suggested dialog response with additional content “set youralarm for then?” This corresponds to scenario 2 above.

In response to the task provider becoming aware of a suggested dialogresponse was sent by the web answers provider, the tasks provider cangenerate another suggested dialog response that refers to the webanswers suggested dialog response with additional content “do you stillwant to set an alarm?” This corresponds to scenario 3 above.

In response to the task provider becoming aware of a suggested dialogresponse was sent by the sports data provider to disambiguate theentity, the tasks provider can generate another suggested dialogresponse that refers to the sports answers suggested dialog responsewith additional content “set your alarm for then?” This corresponds toscenario 4 above.

The various suggested dialog responses from each of the data providersare scored according to the one or more factors. Based on the scoring,the dialog management engine can then select an appropriate dialogresponse. Referring again to the example scenarios above, based on therespective scores that dialog management engine can:

A) Select of the suggested dialog response of the tasks provider(scenario 1)

B) Select an alternative suggested dialog response of the tasks providerand also accept the suggested dialog response of the web answersprovider (scenario 2)

C) Select an alternative suggested dialog response of the tasks providerand also accept the alternative suggested dialog response of the webanswers provider (scenario 3)

D) Select an alternative suggested dialog response of the tasks providerand also accept the suggested dialog response of the sports dataprovider (scenario 4)

E) Select the suggested dialog response of the web answers provider anddrop the alarm state altogether (scenario 5)

F) Select the suggested dialog response of the sports data provider anddrop the alarm state altogether (scenario 6)

G) Generate an entirely new suggested dialog response to ask the userfor their intention (scenario 7). For example, if the scores from thedata providers are not distinguishable by a threshold amount.

Elimination of a suggested dialog response can cascade to othersuggested dialog responses that refer to it. Thus, if the suggesteddialog response of the web answers provider has a disqualifying score,not only is scenario 5 eliminated, but also scenarios 2 and 3. In someimplementations, geographic information can also be used in the scoring.For example, using the geographic information to indicate which Giantsthe user is referring to (San Francisco vs. New York), the sports dataprovider suggested response can be suppressed to eliminate not onlyscenario 6, but also scenario 4.

Embodiments of the subject matter and the operations described in thisspecification can be implemented in digital electronic circuitry, or incomputer software, firmware, or hardware, including the structuresdisclosed in this specification and their structural equivalents, or incombinations of one or more of them. Embodiments of the subject matterdescribed in this specification can be implemented as one or morecomputer programs, i.e., one or more modules of computer programinstructions, encoded on computer storage medium for execution by, or tocontrol the operation of, data processing apparatus. Alternatively or inaddition, the program instructions can be encoded on anartificially-generated propagated signal, e.g., a machine-generatedelectrical, optical, or electromagnetic signal, that is generated toencode information for transmission to suitable receiver apparatus forexecution by a data processing apparatus. A computer storage medium canbe, or be included in, a computer-readable storage device, acomputer-readable storage substrate, a random or serial access memoryarray or device, or a combination of one or more of them. Moreover,while a computer storage medium is not a propagated signal, a computerstorage medium can be a source or destination of computer programinstructions encoded in an artificially-generated propagated signal. Thecomputer storage medium can also be, or be included in, one or moreseparate physical components or media (e.g., multiple CDs, disks, orother storage devices).

The operations described in this specification can be implemented asoperations performed by a data processing apparatus on data stored onone or more computer-readable storage devices or received from othersources.

The term “data processing apparatus” encompasses all kinds of apparatus,devices, and machines for processing data, including by way of example aprogrammable processor, a computer, a system on a chip, or multipleones, or combinations, of the foregoing The apparatus can includespecial purpose logic circuitry, e.g., an FPGA (field programmable gatearray) or an ASIC (application-specific integrated circuit). Theapparatus can also include, in addition to hardware, code that createsan execution environment for the computer program in question, e.g.,code that constitutes processor firmware, a protocol stack, a databasemanagement system, an operating system, a cross-platform runtimeenvironment, a virtual machine, or a combination of one or more of them.The apparatus and execution environment can realize various differentcomputing model infrastructures, such as web services, distributedcomputing and grid computing infrastructures.

A computer program (also known as a program, software, softwareapplication, script, or code) can be written in any form of programminglanguage, including compiled or interpreted languages, declarative orprocedural languages, and it can be deployed in any form, including as astand-alone program or as a module, component, subroutine, object, orother unit suitable for use in a computing environment. A computerprogram may, but need not, correspond to a file in a file system. Aprogram can be stored in a portion of a file that holds other programsor data (e.g., one or more scripts stored in a markup languagedocument), in a single file dedicated to the program in question, or inmultiple coordinated files (e.g., files that store one or more modules,sub-programs, or portions of code). A computer program can be deployedto be executed on one computer or on multiple computers that are locatedat one site or distributed across multiple sites and interconnected by acommunication network.

The processes and logic flows described in this specification can beperformed by one or more programmable processors executing one or morecomputer programs to perform actions by operating on input data andgenerating output. The processes and logic flows can also be performedby, and apparatus can also be implemented as, special purpose logiccircuitry, e.g., an FPGA (field programmable gate array) or an ASIC(application-specific integrated circuit).

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessors, andany one or more processors of any kind of digital computer. Generally, aprocessor will receive instructions and data from a read-only memory ora random access memory or both. The essential elements of a computer area processor for performing actions in accordance with instructions andone or more memory devices for storing instructions and data. Generally,a computer will also include, or be operatively coupled to receive datafrom or transfer data to, or both, one or more mass storage devices forstoring data, e.g., magnetic, magneto-optical disks, or optical disks.However, a computer need not have such devices. Moreover, a computer canbe embedded in another device, e.g., a mobile telephone, a personaldigital assistant (PDA), a mobile audio or video player, a game console,a Global Positioning System (GPS) receiver, or a portable storage device(e.g., a universal serial bus (USB) flash drive), to name just a few.Devices suitable for storing computer program instructions and datainclude all forms of non-volatile memory, media and memory devices,including by way of example semiconductor memory devices, e.g., EPROM,EEPROM, and flash memory devices; magnetic disks, e.g., internal harddisks or removable disks; magneto-optical disks; and CD-ROM and DVD-ROMdisks. The processor and the memory can be supplemented by, orincorporated in, special purpose logic circuitry.

To provide for interaction with a user, embodiments of the subjectmatter described in this specification can be implemented on a computerhaving a display device, e.g., a CRT (cathode ray tube) or LCD (liquidcrystal display) monitor, for displaying information to the user and akeyboard and a pointing device, e.g., a mouse or a trackball, by whichthe user can provide input to the computer. Other kinds of devices canbe used to provide for interaction with a user as well; for example,feedback provided to the user can be any form of sensory feedback, e.g.,visual feedback, auditory feedback, or tactile feedback; and input fromthe user can be received in any form, including acoustic, speech, ortactile input. In addition, a computer can interact with a user bysending documents to and receiving documents from a device that is usedby the user; for example, by sending web pages to a web browser on auser's client device in response to requests received from the webbrowser.

Embodiments of the subject matter described in this specification can beimplemented in a computing system that includes a back-end component,e.g., as a data server, or that includes a middleware component, e.g.,an application server, or that includes a front-end component, e.g., aclient computer having a graphical user interface or a Web browserthrough which a user can interact with an implementation of the subjectmatter described in this specification, or any combination of one ormore such back-end, middleware, or front-end components. The componentsof the system can be interconnected by any form or medium of digitaldata communication, e.g., a communication network. Examples ofcommunication networks include a local area network (“LAN”) and a widearea network (“WAN”), an inter-network (e.g., the Internet), andpeer-to-peer networks (e.g., ad hoc peer-to-peer networks).

The computing system can include clients and servers. A client andserver are generally remote from each other and typically interactthrough a communication network. The relationship of client and serverarises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other. In someembodiments, a server transmits data (e.g., an HTML page) to a clientdevice (e.g., for purposes of displaying data to and receiving userinput from a user interacting with the client device). Data generated atthe client device (e.g., a result of the user interaction) can bereceived from the client device at the server.

While this specification contains many specific implementation details,these should not be construed as limitations on the scope of anyinventions or of what may be claimed, but rather as descriptions offeatures specific to particular embodiments of particular inventions.Certain features that are described in this specification in the contextof separate embodiments can also be implemented in combination in asingle embodiment. Conversely, various features that are described inthe context of a single embodiment can also be implemented in multipleembodiments separately or in any suitable subcombination. Moreover,although features may be described above as acting in certaincombinations and even initially claimed as such, one or more featuresfrom a claimed combination can in some cases be excised from thecombination, and the claimed combination may be directed to asubcombination or variation of a subcombination.

Similarly, while operations are depicted in the drawings in a particularorder, this should not be understood as requiring that such operationsbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. In certain circumstances, multitasking and parallel processingmay be advantageous. Moreover, the separation of various systemcomponents in the embodiments described above should not be understoodas requiring such separation in all embodiments, and it should beunderstood that the described program components and systems cangenerally be integrated together in a single software product orpackaged into multiple software products.

Thus, particular embodiments of the subject matter have been described.Other embodiments are within the scope of the following claims. In somecases, the actions recited in the claims can be performed in a differentorder and still achieve desirable results. In addition, the processesdepicted in the accompanying figures do not necessarily require theparticular order shown, or sequential order, to achieve desirableresults. In certain implementations, multitasking and parallelprocessing may be advantageous.

What is claimed is:
 1. A method comprising: receiving a request, from auser device, associated with performance of a first task, wherein therequest comprises a first voice input of a user of the user device;submitting the request to each of a plurality of distinct dataproviders, wherein each data provider is associated with a distinct datamodel configured to interpret particular types of voice inputs, andwherein the plurality of distinct data providers includes (i) a taskdata provider that directs a dialog toward information used to completea task and (ii) a search data provider; in response to the first voiceinput, receiving a first plurality of suggested dialog responses to thefirst voice input from two or more of the data providers; determining,from the first plurality of suggested dialog responses, a dialog intentof the first voice input and a corresponding first dialog for the firsttask including one or more first dialog responses to provide to the userdevice to complete the first dialog for the first task; receiving asecond voice input in response to providing the one or more first dialogresponses to the user and submitting the second voice input to each ofthe plurality of data providers; receiving a second plurality ofsuggested dialog responses to the second voice input from two or more ofthe data providers, the second plurality of suggested dialog responsesincluding a first suggested dialog response from the search dataprovider and a first suggested dialog response from the task dataprovider, the first suggested dialog response from the task dataprovider being based on the first suggested dialog response from thesearch data provider; for each dialog response of the second pluralityof suggested dialog responses, determining a respective score associatedwith the dialog response; determining a second dialog response based onthe respective scores associated with the second plurality of suggesteddialog responses, the second dialog response being based on both thefirst suggested dialog response from the search data provider and thefirst suggested dialog response from the task data provider; andproviding the second dialog response to the user device.
 2. The methodof claim 1, wherein determining the respective score associated with thedialog response is based on a user personalization model.
 3. The methodof claim 1, wherein determining the respective score associated with thedialog response is based on a respective confidence score that isincluded with the dialog response that is received from one of the dataproviders.
 4. The method of claim 1, comprising: updating a state of thefirst dialog in response to the one or more first dialog responses tothe first voice input; and providing the updated state to the pluralityof data providers as context for analyzing the second voice input.
 5. Asystem comprising: a user device; and one or more computers configuredto interact with the user device and to perform operations comprising:receiving a request, from the user device, associated with performanceof a first task, wherein the request comprises a first voice input of auser of the user device; submitting the request to each of a pluralityof distinct data providers, wherein each data provider is associatedwith a distinct data model configured to interpret particular types ofvoice inputs, and wherein the plurality of distinct data providersincludes (i) a task data provider that directs a dialog towardinformation used to complete a task and (ii) a search data provider; inresponse to the first voice input, receiving a first plurality ofsuggested dialog responses to the first voice input from two or more ofthe data providers; determining, from the first plurality of suggesteddialog responses, a dialog intent of the first voice input and acorresponding first dialog for the first task including one or morefirst dialog responses to provide to the user device to complete thefirst dialog for the first task; receiving a second voice input inresponse to providing the one or more first dialog responses to the userand submitting the second voice input to each of the plurality of dataproviders; receiving a second plurality of suggested dialog responses tothe second voice input from two or more of the data providers, thesecond plurality of suggested dialog responses including a firstsuggested dialog response from the search data provider and a firstsuggested dialog response from the task data provider, the firstsuggested dialog response from the task data provider being based on thefirst suggested dialog response from the search data provider; for eachdialog response of the second plurality of suggested dialog responses,determining a respective score associated with the dialog response;determining a second dialog response based on the respective scoresassociated with the second plurality of suggested dialog responses, thesecond dialog response being based on both the first suggested dialogresponse from the search data provider and the first suggested dialogresponse from the task data provider; and providing the second dialogresponse to the user device.
 6. The system of claim 5, whereindetermining the respective score associated with the dialog response isbased on a user personalization model.
 7. The system of claim 5, whereindetermining the respective score associated with the dialog response isbased on a respective confidence score that is included with the dialogresponse that is received from one of the data providers.
 8. The systemof claim 5, wherein the one or more computers are further configured toperform operations comprising: updating a state of the first dialog inresponse to the one or more first dialog responses to the first voiceinput; and providing the updated state to the plurality of dataproviders as context for analyzing the second voice input.
 9. One ormore non-transitory computer storage media encoded with computer programinstructions that when executed by one or more computers cause the oneor more computers to perform operations comprising: receiving a request,from a user device, associated with performance of a first task, whereinthe request comprises a first voice input of a user of the user device;submitting the request to each of a plurality of distinct dataproviders, wherein each data provider is associated with a distinct datamodel configured to interpret particular types of voice inputs, andwherein the plurality of distinct data providers includes (i) a taskdata provider that directs a dialog toward information used to completea task and (ii) a search data provider; in response to the first voiceinput, receiving a first plurality of suggested dialog responses to thefirst voice input from two or more of the data providers; determining,from the first plurality of suggested dialog responses, a dialog intentof the first voice input and a corresponding first dialog for the firsttask including one or more first dialog responses to provide to the userdevice to complete the first dialog for the first task; receiving asecond voice input in response to providing the one or more first dialogresponses to the user and submitting the second voice input to each ofthe plurality of data providers; receiving a second plurality ofsuggested dialog responses to the second voice input from two or more ofthe data providers, the second plurality of suggested dialog responsesincluding a first suggested dialog response from the search dataprovider and a first suggested dialog response from the task dataprovider, the first suggested dialog response from the task dataprovider being based on the first suggested dialog response from thesearch data provider; for each dialog response of the second pluralityof suggested dialog responses, determining a respective score associatedwith the dialog response; determining a second dialog response based onthe respective scores associated with the second plurality of suggesteddialog responses, the second dialog response being based on both thefirst suggested dialog response from the search data provider and thefirst suggested dialog response from the task data provider; andproviding the second dialog response to the user device.
 10. The one ormore non-transitory computer storage media of claim 9, whereindetermining the respective score associated with the dialog response isbased on a user personalization model.
 11. The one or morenon-transitory computer storage media of claim 9, wherein determiningthe respective score associated with the dialog response is based on arespective confidence score that is included with the dialog responsethat is received from one of the data providers.
 12. The one or morenon-transitory computer storage media of claim 9, further comprisingcomputer program instructions that when executed by the one or morecomputers cause the one or more computers to perform operationscomprising: updating a state of the first dialog in response to the oneor more first dialog responses to the first voice input; and providingthe updated state to the plurality of data providers as context foranalyzing the second voice input.
 13. The method of claim 1, wherein:the first plurality of suggested dialog responses includes a secondsuggested dialog response from the task data provider; and the one ormore first dialog responses include the second suggested dialog responsefrom the task data provider.
 14. The method of claim 1, wherein thesecond plurality of suggested dialog responses further includes a secondsuggested dialog response from the task data provider, the secondsuggested dialog response from the task data provider not being based onthe first suggested dialog response from the search data provider. 15.The method of claim 1, wherein: the plurality of distinct data providersfurther includes an additional data provider; the second plurality ofsuggested dialog responses further includes a first suggested dialogresponse from the additional data provider and a second suggested dialogresponse from the task data provider, the second suggested dialogresponse from the task data provider being based on the first suggesteddialog response from the additional data provider.
 16. The method ofclaim 15, wherein a score associated with the first suggested dialogresponse from the additional data provider does not satisfy a threshold,further comprising, in response to the score associated with the firstsuggested dialog response from the additional data provider notsatisfying the threshold: avoiding basing the second dialog response onthe first suggested dialog response from the additional data provider;and avoiding basing the second dialog response on the second suggesteddialog response from the task data provider.